This repository is used as a ressource for authors wishing to submit to the Melba journal. The repository is structured as follow:
Thank you for submitting to MELBA!
Any new submission to Melba should be accompanied by a cover letter. Authors can use the following template as a starting point:
Dear Editor,
We are happy to submit our manuscript for peer review at the Journal of Machine Learning for Biomedical Imaging (MELBA).
[INSERT TEXT THAT DESCRIBES THE CORE CONTRIBUTIONS OF THE PAPER AND WHY IT WOULD BE SUITABLE FOR MELBA]
[INSERT TEXT THAT CONFIRMS ORIGINALITY] E.g. “The submitted work is original (or a substantially extended version of a conference paper presented at XXXX), is not and will not be under peer review or published elsewhere until an editorial decision has been made by MELBA or the authors > officially withdraw their submission.”
[INSERT TEXT ABOUT ETHICAL DECLARATIONS] E.g. “All the authors mentioned in the manuscript have agreed to authorship, read and approved the manuscript, and given > consent for submission and subsequent publication of the manuscript.” “All data analyzed in this manuscript were collected with appropriate IRB approval and following relevant ethical guidelines”
[INSERT TEXT THAT DISCUSSES CODE AND/OR DATA AVAILABILITY. PLEASE DISCUSS ANY FURTHER ATTEMPTS THAT PROMOTES THE > REPRODUCIBILITY OF THE SUBMITTED WORK] E.g. “The code and data to replicate the results presented in this paper are made publicly available at: XXXX”
If you have questions or concerns, please feel free to ask questions on the Issues board or editors@melba-journal.org, or do Pull Requests where appropriate.
We provide a minimalist latex template, requiring only the melba.sty style file. Samples PDFs, from different stage during the reviewing process, are available:
- submission: to submit a manuscript for review (mandatory, using any other template will result in a desk reject);
- arxiv-submission: to upload a manuscript on arXiv while it is being reviewed (turns off line-numbers);
- accepted: to use once the paper has been accepted and is moving to publication stage;
- accepted in a special issue: to use for accepted paper that belong to a special issue only.
By default, line-numbering is enabled, and any un-needed display (such as issue information) is disabled. During submission, authors should not modify it.
This correspond to the template that we provide 'as-in', authors should not need to modify anything at that stage.
These are the final formatting and submission isntructions for MELBA Accepted papers.
At every step below where we ask for communication or delivery of a file, please use the scholastica Discussions mechanism. The publishing editor will guide you and help you during this process.
- Switch the template option to ‘accepted’ option in the first lines of the latex:
\usepackage[accepted]{melba}; - populate the
\melbaheadingcommand as instructed in the latex comments with the information provided by the publishing editor; - complete the Ethical Standards and Conflicts of Interest sections at the end of the paper;
- upload your final pdf version via the Discussions page;
- please also provide a representative, high-resolution image of your paper—this will act as a graphical abstract on the Melba website;
- (Optional) authors can also send a video presentation of their paper, that would be embedded into the website;
- once validated by the publishing editor, upload this final paper version to arXiv without any further changes. Please do not upload it before you have received final pdf acceptance. The arXiv Comments field must say “Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA) https://www.melba-journal.org”. If you have already uploaded an earlier preprint to arxiv (e.g. if you chose that route for submission to MELBA), please update that version instead of creating a new arXiv submission.
- let us know of the final arXiv preprint ID (e.g. 1809.05231) and version (e.g. v3);
- once this is done, no further updates are permitted to the arxiv submission, as any update would not have been reviewed by the MELBA journal.
Melba has currently the following special issues:
- Medical Imaging with Deep Learning (MIDL) 2020 Guest Editors: Marleen de Bruijne, Tal Arbel, Ismail Ben Ayed, Hervé Lombaert
- Uncertainty for Safe Utilization of Machine Learning in Medical Imaging (UNSURE) 2020 Guest Editors: Christian Baumgartner, Adrian Dalca, Carole Sudre, Ryutaro Tanno, Sandy Wells
- Information Processing in Medical Imaging (IPMI) 2021 Guest Editors: Aasa Feragen, Stefan Sommer, Julia Schnabel, Mads Nielsen